Unverified50% confidenceFactExact time
pass@k is a commonly used metric for measuring sampling quality in tasks such as code generation: k candidate answers are independently sampled for the same problem, and success is counted as long as any one of them passes verification.
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Long-term
Relevance
10/14/2026
First Seen
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Unverifiedpass@k指标衡量模型生成k个候选代码片段时至少有一个能通过全部测试用例的概率79% similarUnverifiedPass@5 is an evaluation metric: generate 5 independent solutions to the same problem, and success is counted if any one of them passes verification; compared with Pass@1, it better reflects the upper limit of capability.74% similarUnverifiedThe pass@k metric is widely adopted on standard benchmarks such as HumanEval and MBPP.73% similarUnverifiedThe pass@k metric was first systematically defined in OpenAI's Codex paper, measuring the probability that at least one of k independent samples for the same problem is correct.70% similar
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